Intel and a team of researchers from the University of Illinois Urbana-Champaign have managed to train AI in low light photo processing to elevate the quality of visuals produced. The technology has managed to develop clearer images than those captured through traditional low light photography techniques.

“Short-exposure images suffer from noise, while long exposure can lead to blurry images and is often impractical. A variety of denoising, deblurring, and enhancement techniques have been proposed, but their effectiveness is limited in extreme conditions, such as video-rate imaging at night,” explains the team.

In the paper titled Learning to See in the Dark submitted on 4 May, the researchers explain how the experiments were conducted using a collection of photo pairs, each comprising one RAW short-exposure nighttime image and its corresponding long-exposure counterpart.

“Experiments demonstrate promising results, with successful noise suppression and correct color transformation on SID data,” writes the team in the paper’s discussion. Nevertheless, they note that further improvements can be made to image quality and that these results are simply the tip of the iceberg.